Molecular mediators of breast cancer bone metastasis
Bibliographic record
Abstract
Breast cancer is the most frequently diagnosed and the second leading cause of cancer deaths in Canadian women. The most devastating and deadly feature of the disease is the emergence of metastases. Breast cancer most commonly metastasizes to bone, often leading to a significantly decreased quality of life in affected patients. Despite progress in understanding the underlying molecular biology of breast tumors that relapse to bone, to date there are no therapies capable of curing the disease. Hence, it is essential to gain a more in-depth knowledge of the molecular mechanisms that underlie the emergence and growth of breast cancer skeletal metastases. Consequently, it was attempted to: 1) examine the efficacy of targeting a known pathway important for breast cancer metastasis to bone, 2) identify novel mediators of this process and 3) develop a stratification tool capable of identifying patients with breast cancer that possesses a high likelihood of spreading to bone. Transforming growth factor-beta (TGF-β) signaling is a potent modulator of the invasive and metastatic behavior of breast cancer cells. The work in this thesis demonstrates that expression of a TGF-β ligand trap, which neutralizes TGF-β1 and TGF-β3 in breast cancer cells, diminished their outgrowth in bone and reduced the severity of osteolytic lesion formation. It is further shown that a reduction or loss of host-derived TGF-β1 reduced the incidence of breast tumor outgrowth in the skeleton. Moreover, tumor cells capable of growing within the bone of a TGF-β1 deficient host up-regulated expression of all three TGF-β isoforms within the tumor cells themselves, effectively bypassing the host-deficiency. Next, a gene discovery approach was undertaken to identify novel candidate mediators of breast cancer skeletal metastasis. Invasive breast epithelium was selectively isolated by laser capture microdissection (LCM) performed on bone metastases and primary tumors from patients displaying breast cancer with subsequent recurrence to the skeleton. In this search, ABCC5 was found to be overexpressed in osseous metastases compared to primary mammary tumors metastatic to bone. Furthermore, this protein was detected at substantially higher levels in human and mouse breast cancer cells, which metastasize to bone in animal models. Importantly, removal of this protein from these cells resulted in their decreased ability to induce osteolytic bone lesions, which was correlated with a decreased recruitment of osteoclasts, cells responsible for the bone resorption process. Finally, the molecular changes occurring within the primary breast tumor were investigated in an attempt to identify a prognostic bone metastatic signature. Gene expression profiling was performed on estrogen receptor (ER)-positive primary breast tumors metastastatic to bone and breast cancers, which spread to soft tissue. A 25-gene signature was derived from the top 100 differentially expressed probes and was found to be capable of discriminating breast tumors metastatic to bone from cancers recurring to visceral sites in an independent gene expression dataset.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.265 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".